← BioTransfer GEO Dataset Finder
GEO series

Genome-wide chromatin recording resolves dynamic cell state changes

GSE305653 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 110 samples Submitted 2026/08/03 Platform GPL34475Platform GPL34295
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 110 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
110 samples: 46 conditions, mostly in duplicateGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Genome-wide chromatin recording resolves dynamic cell state changesbioRxiv : the preprint server for biology · 2026
Summary (written by the submitters)
Understanding how the chromatin state of a cell influences its future behavior is a major challenge throughout biology. However, most chromatin profiling methods are limited to endpoint assays. Here, we present LagTag, a method for recovery of earlier and endpoint chromatin states in the same mammalian cells. In this approach, transient expression of bacterial adenine methyltransferase fusions records the DNA binding profiles of chromatin-associated proteins of interest at earlier timepoints.
Read the full summary ↓
Subsequent tagmentation and sequencing recovers the earlier chromatin profile from adenine methylation profiles, alongside endpoint profiles of endogenous chromatin-associated proteins. We verified that LagTag profiles aligned with those from established methods in mouse and human cells. More importantly, LagTag was able to record and recover dynamic chromatin state transitions during mouse embryonic stem cell differentiation, capturing transcriptional signatures from pre- and post-differentiation timepoints in the same cells. LagTag thus provides a foundation for temporally resolved chromatin profiling.
Published in
Genome-wide chromatin recording resolves dynamic cell state changes
Takei Y, Lay JA, Linton JM et al. · bioRxiv : the preprint server for biology 2026 · PMID 42146680 · doi:10.1101/2025.08.05.668773
This dataset
Open GSE305653 in finder → Find more ChIP / ATAC / CUT&Tag datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE305653_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1307425 and SRA study SRP610089. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42146680) ↗
Study design
46 conditions, mostly in duplicate
E14, LagTag, EspM-TAF3x3, ×3 E14, LagTag, M.EcoGII-LMNB1, ×3 E14, LagTag, M.EcoGII-RNAPIISer2p_mintbody, ×3 E14, LagTag, M.EcoGII-mCherry, ×3 mESC-Gata4, CUT&Tag, RNAPIISer2p, differentia… ×3 mESC-Gata4, CUT&Tag, RNAPIISer2p, pluripotent, ×3 mESC-Gata4 (M.EcoGII-RNAPIISer2_mintbody), CU… ×3 mESC-Gata4 (M.EcoGII-RNAPIISer2_mintbody), CU… ×3 +38 more

Supports a between-group comparison across 110 samples.

How we read this: 46 replicated groups read from 110 sample titles; they account for 110 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 70 more — browse all 110 samples with per-sample file links →

Datasets on a similar topic

Search all ChIP / ATAC / CUT&Tag datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.